Modulation of neural networks is a common means of providing flexibility to behaviors of all animals, including humans and insects. Neuromodulation is critical for development, and for the proper functioning of many physiological processes, ranging from cognition and light adaptation to gastric motor activity. Many human diseases arise from neuromodulatory disorders, necessitating a better understanding of neuromodulation. Many of the cellular properties of the neurons involved in modulating these behaviors appear to be fundamental to all neural systems, but they are still not fully understood. The current interests of this lab include understanding the dynamics of neural networks, and the modulation of behaviors. In particular, insect ecdysis, or the shedding of the old cuticle at each molt depends on neural and hormonal control of stereotyped behaviors. The moth, Manduca sexta, has been a model system for the study of growth and development for decades, as the "white rat" of insect endocrinology, and is therefore ideal for studying the neural control of ecdysis in particular, and neuromodulation in general. Previous localization of inhibitory elements that modulate the ecdysis cascade in Manduca have suggested that identification of the inhibitory neurons will provide a model system for studying neuromodulation. This proposal outlines experiments aimed at identifying and characterizing the inhibitory neurons, as well as characterizing the cellular responses of this modulatory network, along with downstream targets involved in ecdysis. Using electrophysiology, including extra-and intracellular techniques, the inhibitory neurons and their actions within this neural network will be characterized. In vivo responses to cell isolation or ablation will also be analyzed using a combination of time lapse videography and confocal microscopy. Concurrently, modified peptide analogues will be tested for their ability to cross the blood brain barrier, as tools for the current research, and to study structure/activity relationships of various transmitters of this neural network.